摘要
在葡萄苗木嫁接时,切削刀的技术参数,如刀刃参数、切削速度、切削方式等,直接影响了切削面的粗糙度,继而影响了成活率。因而,根据工业中零部件粗糙度的定义,确定了葡萄苗木粗糙度的检测评定,遵从国家标准GB/T 3505—2009规定的用"轮廓法确定表面结构",采用GB/T 12472-2003标准,确定葡萄切削面粗糙度的评定规则,计算其轮廓算术平均偏差(Ra)、轮廓最大高度(Rz)、单个微观不平度高度与在测量长度上的平均值(Rpv),来计算切削面粗糙度值。在此基础上,综合分析了现有粗糙度检测的国家标准、检测方法、图像检测技术,提出了采用图像处理技术对葡萄苗木切削面粗糙度进行无损检测,可以确定切削技术参数,提高嫁接成活率,为后续的自动化嫁接技术提供技术支撑。
Grape is one of the most important fruits in our country, and grape seedling grafting is an important guarantee to im- prove the quality of grapes. In grape seedling grafting, the technical parameters of cutting knife, such as blade parameters, cut- ting speed and cutting methods, etc., directly affect the cutting surface roughness, and then, affect the survival rate. In this pa- per, detection and evaluation of the rough degree of grape seedlings were determined according to the definition of the roughness of parts in industry. And complied with the national standard GB/T 3505 - 2009 of the provisions of the ＂contour method to de- termine the surface structure＂, using GB / T 12472-2003 standard, the grape cutting surface roughness evaluation rules were determine, and the cutting surface roughness was calculated by calculating contour arithmetic mean deviation （Ra）, contour maximum height （Rz）, individual microscopic roughness height and the average value of the measured length （Rpv）. On this basis, this paper comprehensively analyzed the existing national standards, detection methods and image detection technology, and put forward to adopt image processing technology for grape seedling cutting surface roughness nondestructive testing. This method can determine the cutting technology parameters, improve the survival rate of grafting and provide technical support for the subsequent automation grafting technology.
出处
《农业装备与车辆工程》
2017年第4期6-10,20,共6页
Agricultural Equipment & Vehicle Engineering
基金
北京市自然科学基金资助项目(6152012)
关键词
葡萄嫁接
苗木切削
切削面粗糙度
轮廓算术平均偏差
图像处理技术
grape grafting
seedling cutting
cutting surface roughness
contour arithmetic mean deviation
image processingtechnology
作者简介
徐丽明，女，山东蓬莱人，教授，博士生导师，主要从事生物生产自动化技术与装备研究。E-mail：xlmoffiee@126．com
